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datadog-mcp-server

update-spans-metric

Modify a span-based metric's filter query, group-by fields, or percentile aggregations to adjust APM data aggregation.

Instructions

Update a span-based metric's filter, group-by, or percentile settings

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
metricIdYesThe name of the span-based metric to update
includePercentilesNoWhether to include percentile aggregations. Only for distribution metrics
filterQueryNoUpdated APM search query to filter spans
groupByNoUpdated fields to group the metric by
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description bears full burden for behavioral transparency. It only states 'Update' without disclosing side effects, idempotency, or required permissions. The description does not indicate whether changes are immediately applied or what happens to existing configurations not specified in the request.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single sentence of only 8 words conveys the core purpose without wasted text. It is well front-loaded and efficiently communicates the tool's function.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the tool's primary function but lacks details on the response format (no output schema), whether updates are partial or full, and any prerequisites. For a mutation tool with no annotations, more context is needed to ensure proper usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents each parameter's purpose. The description summarizes the parameters (filter, group-by, percentile) but adds no additional meaning beyond what the schema provides. Baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states the action ('Update') and the resource ('span-based metric') along with the specific aspects that can be modified ('filter, group-by, or percentile settings'). This clearly distinguishes it from sibling tools like create-spans-metric or update-logs-metric.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool is for updating existing span-based metrics, but it does not provide explicit guidance on when to use this tool versus alternatives (e.g., create-spans-metric for new metrics) or when not to use it (e.g., if the metric type is not span-based). No exclusions or context are given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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